Pankaj Daga

2.3k total citations
47 papers, 1.3k citations indexed

About

Pankaj Daga is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Pankaj Daga has authored 47 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Pankaj Daga's work include Advanced Neuroimaging Techniques and Applications (8 papers), Advanced MRI Techniques and Applications (7 papers) and Medical Image Segmentation Techniques (6 papers). Pankaj Daga is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (8 papers), Advanced MRI Techniques and Applications (7 papers) and Medical Image Segmentation Techniques (6 papers). Pankaj Daga collaborates with scholars based in United States, United Kingdom and India. Pankaj Daga's co-authors include Sébastien Ourselin, David M. Cash, Marc Modat, Robert J. Doerksen, John S. Duncan, Gavin P. Winston, Nurulain T. Zaveri, Alexandra L. Young, Neil P. Oxtoby and Nick C. Fox and has published in prestigious journals such as PLoS ONE, Brain and Annals of Neurology.

In The Last Decade

Pankaj Daga

45 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pankaj Daga United States 20 372 315 198 195 193 47 1.3k
Étienne Lessard United States 24 213 0.6× 483 1.5× 54 0.3× 110 0.6× 144 0.7× 59 1.9k
Yong Ji China 22 409 1.1× 96 0.3× 237 1.2× 583 3.0× 122 0.6× 81 1.5k
Ahmadul Kadir Sweden 16 343 0.9× 178 0.6× 380 1.9× 659 3.4× 248 1.3× 18 1.4k
Yu‐Fen Wang China 25 996 2.7× 250 0.8× 42 0.2× 79 0.4× 47 0.2× 98 2.6k
Huaqiao Wang China 21 468 1.3× 179 0.6× 59 0.3× 253 1.3× 50 0.3× 70 1.2k
Pei Huang China 22 720 1.9× 159 0.5× 90 0.5× 358 1.8× 185 1.0× 79 1.9k
Ghanim Ullah United States 28 716 1.9× 645 2.0× 129 0.7× 286 1.5× 897 4.6× 82 2.6k
Hongming Li United States 22 167 0.4× 436 1.4× 149 0.8× 41 0.2× 14 0.1× 96 1.6k
László Kovács Hungary 26 879 2.4× 181 0.6× 23 0.1× 175 0.9× 465 2.4× 135 2.4k
Jesús Giraldo Spain 26 1.5k 4.1× 113 0.4× 33 0.2× 264 1.4× 1.0k 5.3× 120 2.4k

Countries citing papers authored by Pankaj Daga

Since Specialization
Citations

This map shows the geographic impact of Pankaj Daga's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pankaj Daga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pankaj Daga more than expected).

Fields of papers citing papers by Pankaj Daga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pankaj Daga. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pankaj Daga. The network helps show where Pankaj Daga may publish in the future.

Co-authorship network of co-authors of Pankaj Daga

This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj Daga. A scholar is included among the top collaborators of Pankaj Daga based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pankaj Daga. Pankaj Daga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Clark, Robert D. & Pankaj Daga. (2019). Building a Quantitative Structure-Property Relationship (QSPR) Model. Methods in molecular biology. 1939. 139–159. 7 indexed citations
2.
Daga, Pankaj, Michael B. Bolger, Ian S. Haworth, Robert D. Clark, & Éric Martin. (2018). Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series. Molecular Pharmaceutics. 15(3). 821–830. 21 indexed citations
3.
4.
Daga, Pankaj, François Chadebecq, Stephen Thompson, et al.. (2016). A Combined EM and Visual Tracking Probabilistic Model for Robust Mosaicking: Application to Fetoscopy. UCL Discovery (University College London). 524–532. 9 indexed citations
5.
Mancini, Laura, W.D. Penny, Guillaume Flandin, et al.. (2015). Objective Bayesian fMRI analysis—a pilot study in different clinical environments. Frontiers in Neuroscience. 9. 168–168. 5 indexed citations
6.
Daga, Pankaj, Ninon Burgos, Mark White, et al.. (2015). Simulated field maps for susceptibility artefact correction in interventional MRI. International Journal of Computer Assisted Radiology and Surgery. 10(9). 1405–1416. 4 indexed citations
7.
Daga, Pankaj, Marc Modat, Mark White, et al.. (2014). Susceptibility artefact correction using dynamic graph cuts: Application to neurosurgery. Medical Image Analysis. 18(7). 1132–1142. 12 indexed citations
8.
Young, Alexandra L., Neil P. Oxtoby, Pankaj Daga, et al.. (2014). A data-driven model of biomarker changes in sporadic Alzheimer's disease. Brain. 137(9). 2564–2577. 183 indexed citations
9.
Fu, Gang, Xiaofei Nan, Haining Liu, et al.. (2012). Implementation of multiple-instance learning in drug activity prediction. BMC Bioinformatics. 13(S15). S3–S3. 27 indexed citations
10.
Liu, Sheng, Ronak Y. Patel, Pankaj Daga, et al.. (2012). Combined Rule Extraction and Feature Elimination in Supervised Classification. IEEE Transactions on NanoBioscience. 11(3). 228–236. 14 indexed citations
11.
Winston, Gavin P., Pankaj Daga, Jason Stretton, et al.. (2011). Optic radiation tractography and vision in anterior temporal lobe resection. Annals of Neurology. 71(3). 334–341. 69 indexed citations
12.
Nan, Xiaofei, Gang Fu, Sheng Liu, et al.. (2011). Leveraging domain information to restructure biological prediction. BMC Bioinformatics. 12(S10). S22–S22. 2 indexed citations
13.
Daga, Pankaj, Ronak Patel, & Robert J. Doerksen. (2010). Template-Based Protein Modeling: Recent Methodological Advances. Current Topics in Medicinal Chemistry. 10(1). 84–94. 33 indexed citations
14.
Daga, Pankaj, Jinsong Duan, & Robert J. Doerksen. (2010). Computational model of hepatitis B virus DNA polymerase: Molecular dynamics and docking to understand resistant mutations. Protein Science. 19(4). 796–807. 30 indexed citations
15.
Ahmed, Safwat A., et al.. (2009). Semisynthetic latrunculin B analogs: Studies of actin docking support a proposed mechanism for latrunculin bioactivity. Bioorganic & Medicinal Chemistry. 17(21). 7517–7522. 7 indexed citations
16.
Daga, Pankaj & Robert J. Doerksen. (2008). Stereoelectronic properties of spiroquinazolinones in differential PDE7 inhibitory activity. Journal of Computational Chemistry. 29(12). 1945–1954. 24 indexed citations
17.
Sivaprakasam, Prasanna, Pankaj Daga, Aihua Xie, & Robert J. Doerksen. (2008). Glycogen synthase kinase-3 inhibition by 3-anilino-4-phenylmaleimides: insights from 3D-QSAR and docking. Journal of Computer-Aided Molecular Design. 23(2). 113–127. 20 indexed citations
18.
Singh, Sunil K., et al.. (2004). Synthesis and biological evaluation of 2,3-diarylpyrazines and quinoxalines as selective COX-2 inhibitors. Bioorganic & Medicinal Chemistry. 12(8). 1881–1893. 58 indexed citations
19.
Thaimattam, Ram, et al.. (2004). 3D-QSAR CoMFA, CoMSIA studies on substituted ureas as Raf-1 kinase inhibitors and its confirmation with structure-based studies. Bioorganic & Medicinal Chemistry. 12(24). 6415–6425. 18 indexed citations
20.
Daga, Pankaj, et al.. (1988). A review of large biochemistry analysers. Journal of Analytical Methods in Chemistry. 10(1). 43–61. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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